Course overview (see schedule) + ‘housekeeping’

Day 1

• 09:30-10:00 Introduction
• 10:00-11:00 Development environments, system commands, and version control
  
• 11:15-12:30 Sharing code and data
  
• 13:30-15:00 Reproducible papers and documentation with Quarto
  
• 15:15-16:30 Cross-references and citations with Quarto

Day 2

• 09:30-10:30 Drafting a reproducible paper
  
• 10:45-12:30 Generating reproducible publication-quality visualisations
  
• 13:30-14:30 Editing other people’s work
  
• 14:45-16:00 Working on papers -> Presentations and wrap-up

About us

Robin Lovelace

• Professor of Transport Data Science
• Focus: influencing decision-making, to make it more evidence-based
• R package developer and data scientist
• New methods for more reproducible, data-driven and participatory transport planning

Juan Fonseca

• PhD student at the University of Leeds
• Focus: fast and flexible models for estimating traffic
• Developer of {Telraamr} and {azuremapsr} R packages, the latter of which was recently published on CRAN

About you

• Name
• What tools you currently use for research
• Where you’re from
• What’s your favourite animal
• A random fact about you

Me

• Currently using VS Code, Quarto, R, Google Gemini etc, Devcontainers
• From Herefordshire, UK
• Favourite animal: Red kite
• Random fact: I run 5 km every Saturday with double buggy

Over to you

The origins of the course

“If only I was told this ealier in my career”

Imagine a workflow that enabled:

• Fewer context switches
• More focus on the content and not style of the work
• Integration of code into your research manuscript
• Automatic generation of results, including figures and tables…
  • That change seamlessly when input datasets or code changes
• Control over how you export and publish your work
  • Including publication-quality PDFs, website, blogs, slides
• Full reproducibility
• You to share your work for maximum benefit to others

Reproducible research

Example of reproducible research: networkmerge

See paper website: https://nptscot.github.io/networkmerge/

Example: rs5c conference slides

See slides website: https://robinlovelace.github.io/rs5c/

Example: biclaR

See https://github.com/U-Shift/biclar

Course principles

• “Learn by doing”
• “Learn by teaching”
• “Learn from each other”
• “We’re all learning”
• “Growth mindset”
• “Can-do” and “Go for It” attitude
• “Every error is a learning opportunity”
• “No such thing as a bad question”
• “Fail fast”
• Balance between focused work and comms
• Bring you own principles (BYOP)

The practical sessions

• Time of in-depth work
• Use the course website as a reference point but spend most of the time in your own environment
• Juan and I will support people 1-2-1 and do ‘live demos’ now and then

Any questions before we move to the first practical?

Session 1 introduction (see Session 1 workbook)

• 09:30-10:00 Introduction
• 10:00-11:00 Development environments, system commands, and version control
  
• 11:15-12:30 Sharing code and data
  
• 13:30-15:00 Reproducible papers and documentation with Quarto
  
• 15:15-16:30 Cross-references and citations with Quarto

Day 2

• 09:30-10:30 Drafting a reproducible paper
  
• 10:45-12:30 Generating reproducible publication-quality visualisations
  
• 13:30-14:30 Editing other people’s work
  
• 14:45-16:00 Working on papers -> Presentations and wrap-up

Live demo of VS Code

Git and the GitHub CLI

Principle: the command-line is better than the graphical user interface (CLI > GUI)

• Using a GUI may allowing you to do something quicker the first time but will slow you down in the long-run

• CLI: hard first time¹ but will save time in long term

• The relationship between git and gh tools

  • git is a long-established version-control system with many commands
  • gh is a high-level interfact to git and the GitHub platform

Live demo: cloning repos, opening issues, Pull Requests from CLI

```bash

Solo working through the practical (until ~11:00)